iSVP: an integrated structural variant calling pipeline from high-throughput sequencing data

摘要

Background Structural variations (SVs), such as insertions, deletions, inversions, and duplications, are a common feature in human genomes, and a number of studies have reported that such SVs are associated with human diseases. Although the progress of next generation sequencing (NGS) technologies has led to the discovery of a large number of SVs, accurate and genome-wide detection of SVs remains challenging. Thus far, various calling algorithms based on NGS data have been proposed. However, their strategies are diverse and there is no tool able to detect a full range of SVs accurately.